With the rapid growth of such networks as the Internet, the accuracy and quality of searches becomes more and more important. However, many users find that searching using search engines yields a large number (perhaps thousands) of results, many of which are not closely applicable to their submitted query. As such, many users become dissatisfied with the search results. Some users also find that the large number of returned results for queries obscure important information contained in the Internet.
Most prior-art search engines are primarily based on a keyword comparison. Consider a query asking for the top N digital camera manufacturers in the world, where N is an integer. Keyword comparison search engines would return some Web pages that contain the key term “digital camera” and other Web pages that contain the key term “manufacturers”. Therefore, the percentage of the total returned results that relate to digital camera manufacturers that are returned in keyword comparison search engines is relatively small. The keyword comparison search engine also has no way to compare whether a particular digital camera manufacturer is larger or better known (or some other quantifiable comparison) than another digital camera manufacturer based on their Web pages. As such, prior-art search engines, being primarily based on keyword comparisons, often lead to the large number of results many of which are marginally related to the query. Such keyword comparison search engines cannot identify the most applicable ones of a plurality of searched Web sites based on the structure of the Web sites.
In another aspect, many users believe that they have to search through a large number of queries to obtain useful search results. As such, the users believe that the queries (and the examination of the search results for relevancy) demand a considerable amount of time to ensure that all relevant responses are considered. Even after such time is spent, the users often believe that the most significant search results may be lost within a vast amount of irrelevant information.
In yet another aspect, many Internet applications utilize such lexicography tools as WordNet® (developed at Princeton University under the direction of Prof. George A. Miller) to expand the user's query to improve the precision of the search engine. WordNet is an online lexical reference system. With WordNet, nouns, verbs, adjectives and adverbs are organized into synonym sets, each representing one underlying lexical concept. Different relationships link the synonym sets. With WordNet, users manually input their personal taxonomy relative to Web pages. Therefore, WordNet is not suitably configured to keep up with the rapid growth and dynamic changes of Internet and other networked computer systems. For example, over half of the words in the Web do not appear in WordNet.